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Assessing the Global and Local Uncertainty of Scientific Evidence in the Presence of Model Misspecification

Frontiers in Ecology and Evolution(2021)10.3389/fevo.2021.679155Source: DataRank Database

Assessing the Global and Local Uncertainty of Scientific Evidence in the Presence of Model Misspecification is a research paper published in Frontiers in Ecology and Evolution (2021). On theSindex it has a DataRank of 0. It has been cited 1 time.

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0DataRank · unranked

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Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 0.21)OA: goldTopics (37)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (5)

Subhash R. Lele,José-Miguel Ponciano,Brian Dennis ORCID,Christopher L. Jerde ORCID,Mark L. Taper

Live enrichment

PubMed:19767382 OpenAlex:https://openalex.org/W3135944085

National Institutes of Health

Grant: 1R01GM103604-01

Genetic regulation

National Institutes of Health

Grant: 1R01GM117617-01

Spatio-temporally explicit estimation of R0 for pathogens with environmentally-mediated transmission

FWCI

0.21

Citation Percentile

0.5%

Citation Trend

2023

goldLicense: cc-by

journalhttps://www.frontiersin.org/articles/10.3389/fevo.2021.679155/pdf

GOLDhttps://www.frontiersin.org/articles/10.3389/fevo.2021.679155/pdf

publisherhttps://www.frontiersin.org/articles/10.3389/fevo.2021.679155/pdf

publisherhttps://www.frontiersin.org/articles/10.3389/fevo.2021.679155/full

journalhttps://doi.org/10.3389/fevo.2021.679155

Fields of Study

Advanced Statistical Methods and ModelsData Analysis with RWater Quality and Resources StudiesComputer SciencePhysicsMathematics01 natural sciences0101 mathematics

Keywords

EstimatorEconometricsSampling distributionSampling (signal processing)InferenceParametric statisticsIdentification (biology)Computer scienceEmpirical distribution functionStatistical inferenceParametric modelUncertainty quantificationStatisticsMathematicsMachine learningArtificial intelligenceEcologyFOS: Computer and information sciencesmodel selectionEvolutionnon-parametric bootstrapunconditional and conditional inferenceMethodology (stat.ME)QH359-425evidential confidence intervalsinformation criteriapre- and post-data inferenceQH540-549.5Statistics - Methodology

Sustainable Development Goals

SDG 0: Peace, Justice and strong institutions